Analysis of Agricultural Commodity Potential in Braja Yekti Village Using the Location Quotient (LQ) Method Based on Geographic Information System (GIS)
DOI:
https://doi.org/10.59261/jiosjournal.v2i2.25Keywords:
Location Quotient, Geographic Information System, Agricultural Commodity, Base Commodity, Spatial AnalysisAbstract
Braja Yekti Village, East Lampung Regency, has diverse agricultural commodities, yet village development planning has not been supported by evidence identifying commodities with comparative advantages or by spatial information showing their distribution across hamlets. This study aimed to identify leading agricultural commodities using the Location Quotient (LQ) method and to visualize their spatial distribution through a Geographic Information System (GIS). A quantitative descriptive, cross-sectional spatial approach was employed using 2024 harvested-area data for nine agricultural commodities across five hamlets. Secondary data were obtained from the village agricultural extension office and the East Lampung Regency Central Bureau of Statistics, while primary data were collected through field observations and semi-structured interviews with five farmer group leaders. Harvested-area data were analyzed using the LQ method and visualized in QGIS. The findings indicate that seven commodities corn, cassava, peanut, chili, long bean, rambutan, and coconut obtained average LQ values above one, whereas paddy and banana were classified as non-base commodities. Cassava recorded the highest average LQ value (2.78), with strong spatial concentration in Dusun III and Dusun IV. However, several commodities showed LQ values close to the classification threshold and varied among hamlets, requiring careful interpretation. The integration of LQ and GIS provides a spatially explicit evidence base to support village governments in prioritizing commodity-specific agricultural development and location-based planning.